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    "story_id": "mp-2026-09-26-003",
    "source_story_id": "tmp-story-action-discriminative-world-model",
    "edition_id": "mp-2026-09-26-morning-0079",
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    "section": "robotics",
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    "headline": "A World Model Learned to Tell Actions Apart",
    "slug": "a-world-model-learned-to-tell-actions-apart",
    "dek": "AD-WM raised hard-start success from 3.7% to 52.0% and real-robot pick-and-place from 42.2% to 71.1%.",
    "summary": "AD-WM raised hard-start success from 3.7% to 52.0% and real-robot pick-and-place from 42.2% to 71.1%.",
    "body_text": "Most world models minimize error on the transition that actually happened, even though model-predictive control must compare several actions from the same state. AD-WM adds action-recovery objectives during training, then discards their auxiliary heads at test time. Against a matched latent-world-model baseline, the authors report gains in four of five simulated environments and zero-shot transfer to a Franka setup without lab-specific adaptation. The results belong to the tested tasks and encoders; they support action discrimination as a planning objective rather than a general robotics guarantee.",
    "why_it_matters": "AD-WM raised hard-start success from 3.7% to 52.0% and real-robot pick-and-place from 42.2% to 71.1%.",
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    "importance": 9,
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    "first_published_at": "2026-09-26T09:00:00.000-04:00",
    "modified_at": "2026-09-26T09:00:00.000-04:00",
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        "text": "AD-WM raised hard-start success from 3.7% to 52.0% and real-robot pick-and-place from 42.2% to 71.1%.",
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    "tags": [
      "world models",
      "model-predictive control",
      "robot manipulation"
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  "sources": [
    {
      "source_id": "source-2026-09-26-003",
      "title": "arXiv preprint 2609.30264",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2609.30264",
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      "source_type": "primary_research",
      "is_primary_source": true,
      "published_at": "2026-09-24T13:59:41.000-04:00",
      "accessed_at": "2026-09-26T08:20:31.000-04:00",
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  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "A World Model Learned to Tell Actions Apart",
    "publisher": "The Machine Press",
    "published_at": "2026-09-26T09:00:00.000-04:00",
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